Triple
T20254253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthony LaPaglia |
E498643
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Summer of Sam |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Summer of Sam | Statement: [Anthony LaPaglia, notableWork, Summer of Sam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Summer of Sam Context triple: [Anthony LaPaglia, notableWork, Summer of Sam]
-
A.
Summer of Sam
chosen
Summer of Sam is a 1999 crime thriller film directed by Spike Lee that dramatizes the fear and paranoia in New York City during the 1977 Son of Sam murders.
-
B.
House of Sam
House of Sam is a creative collective or brand linked to the artist Zal, known for its distinctive, collaborative artistic identity.
-
C.
Son of Sam
Son of Sam is the nickname given to American serial killer David Berkowitz, who terrorized New York City in the mid-1970s with a series of shootings.
-
D.
Boogeyman
Boogeyman is a 2005 supernatural horror film about a man confronting the childhood monster he believes killed his father.
-
E.
The Babysitter
The Babysitter is a 2017 American horror-comedy film about a young boy who discovers his attractive babysitter is part of a satanic cult.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673aa42348190852ae8313f4494ca |
completed | April 20, 2026, 6:42 p.m. |
Created at: April 11, 2026, 11:41 p.m.